We performed a comparison between Snowflake and Teradata Cloud Data Warehouse based on real PeerSpot user reviews.
Find out what your peers are saying about Snowflake Computing, Microsoft, Amazon Web Services (AWS) and others in Cloud Data Warehouse."It is a very well-distributed system. It has different data engines for different applications. Many applications can use different computational engines at the same time. In terms of data processing, the feeling was similar to working with a relational database but in a scalable way."
"Snowflake's most valuable features are data enrichment and flattening."
"The querying speed is fast."
"It's ultra-fast at handling queries, which is what we find very convenient."
"The snapshot feature is good, the rollback feature is good and the interface is user-friendly."
"The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management. It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure."
"A user-friendly and reliable solution."
"The solution speeds up the process of onboarding."
"The cloud is ten times better than physical hardware; it is more cost-effective and the upgrade process is ten times easier."
"The most valuable feature is the ease of running queries."
"The product is reliable."
"There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was."
"They have a new console, but I couldn't figure out anything in the new console. So, if I shift to the old console, I can figure out where to create the database schema and other things, but I have no idea where to go in the new console. That's one thing they can improve. I don't know why they created a new console to confuse. The old, classic console is much better."
"The UI could improve because sometimes in the security query the UI freezes. We then have to close the window and restart."
"The complexity of the initial setup of Snowflake depends on the use case. However, Snowflake itself, we don't set it up. The difficulty comes from the ingestion patterns, depending on what data I'm putting in, what kind of enrichment, and what additional value we have to add. However, it does tend to get complex because we have a lot of semi-structured data which we need to handle in Snowflake. There have been some challenges."
"The aspect of it that was more complicated was stored procedures. It does not support SQL language-based stored procedures. You have to write in JavaScript. If they supported SQL language and stored procedures, it would make migration from on-prem much simpler. In most cases, if an on-prem solution has stored procedures, they're usually written in SQL. They're not written as what most on-prem DBMS would refer to as an external stored procedure, which is what these feel like to most people because they're written in a language outside of SQL."
"Sometimes it can be tricky to manage multiple environments if you're purely using Snowflake as your scripting and pipeline environment."
"In future releases, it can also support full unstructured data."
"Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway."
"The cost of Teradata Cloud Data Warehouse has room for improvement."
"Stability-wise, we have had some issues with automation and the ability to handle large datasets."
"It could be a bit more user-friendly."
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Snowflake is ranked 1st in Cloud Data Warehouse with 92 reviews while Teradata Cloud Data Warehouse is ranked 13th in Cloud Data Warehouse with 3 reviews. Snowflake is rated 8.4, while Teradata Cloud Data Warehouse is rated 8.0. The top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". On the other hand, the top reviewer of Teradata Cloud Data Warehouse writes "Is quick, easy to upgrade, and cost-effective". Snowflake is most compared with BigQuery, Azure Data Factory, Teradata and Vertica, whereas Teradata Cloud Data Warehouse is most compared with Amazon Redshift, Teradata, Oracle Exadata, Microsoft Azure Synapse Analytics and Vertica.
See our list of best Cloud Data Warehouse vendors and best Data Warehouse vendors.
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